We already know enough to model the climate. We can do it with astounding accuracy—to the hundredth of a degree and not just 100 years hence but even billions of years into the future. Modeling is not the challenge; accuracy is what we don’t have.
The variation in cosmic ray flux is a key variable. Its affect on the Earth’s climate depends on solar activity. Accordingly, we know what causes climate change: nominally it is the sun, stupid.
With just this much knowledge the Old Farmer’s Almanac provides a more accurate prediction of future climate than all of the Climatists put together. Weather and by extension the climate is nominally related to the Sun’s solar cycle and factoring in what we know about the Sun provides meaningful information. But, Climatists ignore the Sun and many other related variables that also affect climate—like the effects of cosmic ray flux and changes in the polarity and variability of the Earth’s magnetic field.
Changes in the amount of cosmic rays that bathe the Earth as it dashes through the leftovers of busted stars is like having a galactic gravestone fall on your toe. You can’t ignore that, right? Assuming they even care there is only one sane and rational answer as to why Climatists fail to take account of it: because there is not enough computing power on Earth to recon with it so we must put that variable on ignore.
GCMs (General Circulation Models) lack substance because they ignore a lot of important things. GCMs are illusionary. No one should consider GCMs as conforming to some established and supposedly proper methodology. That is why they are therefore more social than scientific. They are not natural. And, the character of GCMs will never have more substance than the characters that fabricate them who then pass them off as a reliable snapshot of future reality.
It is important to admit simple truths about Climatists when the truth is right in front of us. For starters, in truth the grid blocks that are used in the constructions of GCMs are too large. They cannot accurately simulate any of the real-world climate conditions such as thunderstorms, hurricanes and other natural processes that transfer huge amounts of energy from the surface of the Earth to the stratosphere. How can we fix this shortcoming? Needless to say there are no ‘parameters’ that can be applied to stand in for what is missing – to account for what cannot be captured or quantified or even conceptualized – and then call the result reality.
We use simple approximations of real-world activity because the limited computing power that we have at our disposal does not allow us to do more. That GCMs really have the ability to accurately represent actual, observable physical processes is an impossible idea. The only reason the `parameters’ that are selected are used is simply to make GCMs agree with empirical data. The resulting GCMs we get using this method cannot then be used as evidence of reality as if we have captured nature in a bottle. Does anyone believe we can use such GCMs to foretell the future? If so, there is an oracle of Delphi that knows your future.
“ ‘[P]arameterization’ is the process of constructing empirically-based procedures that account for the significant large-scale effects of processes that cannot be resolved (i.e., represented within the computational scheme) because of basic limits in computational power. These limits are induced by the scope of the climate modeling problem. Empirical parameterizations are not unique. Because empirical parameterizations can be invented to force a model to match observations, the ability of a model to represent observed conditions cannot be cited as grounds for confidence in the model’s physical realism. (Independent Summary for Policymakers—IPCC Fourth Assessment Report)